Selective sweeps can increase genetic differentiation among populations and cause allele frequency spectra to depart from the expectation under neutrality. We present a likelihood method for detecting selective sweeps that involves jointly modeling the multilocus allele frequency differentiation between two populations. We use Brownian motion to model genetic drift under neutrality, and a deterministic model to approximate the effect of a selective sweep on single nucleotide polymorphisms (SNPs) in the vicinity. We test the method with extensive simulated data, and demonstrate that in some scenarios the method provides higher power than previously reported approaches to detect selective sweeps, and can provide surprisingly good localization of the position of a selected allele. A strength of our technique is that it uses allele frequency differentiation between populations, which is much more robust to ascertainment bias in SNP discovery than methods based on the allele frequency spectrum. We apply this method to compare continentally diverse populations, as well as Northern and Southern Europeans. Our analysis identifies a list of loci as candidate targets of selection, including well-known selected loci and new regions that have not been highlighted by previous scans for selection.

Modern humans have occupied almost all possible environments globally since exiting Africa about 100,000 years ago. Both behavioral and biological adaptations have contributed to their success in surviving the rigors of climatic extremes, including cold, strong ultraviolet radiation, and high altitude. Among these environmental stresses, high-altitude hypoxia is the only condition in which traditional technology is incapable of mediating its effects. Inhabiting at >3,000-m high plateau, the Tibetan population provides a widely studied example of high-altitude adaptation. Yet, the genetic mechanisms underpinning long-term survival in this environmental extreme remain unknown. We performed an analysis of genome-wide sequence variations in Tibetans. In combination with the reported data, we identified strong signals of selective sweep in two hypoxia-related genes, EPAS1 and EGLN1. For these two genes, Tibetans show unusually high divergence from the non-Tibetan lowlanders (Han Chinese and Japanese) and possess high frequencies of many linked sequence variations as reflected by the Tibetan-specific haplotypes. Further analysis in seven Tibetan populations (1,334 individuals) indicates the prevalence of selective sweep across the Himalayan region. The observed indicators of natural selection on EPAS1 and EGLN1 suggest that during the long-term occupation of high-altitude areas, the functional sequence variations for acquiring biological adaptation to high-altitude hypoxia have been enriched in Tibetan populations.

Background: The coronavirus disease 2019 (COVID‐19) is rapidly spreading in China and more than 30 countries over last two months. COVID‐19 has multiple characteristics distinct from other infectious diseases, including high infectivity during incubation, time delay between real dynamics and daily observed number of confirmed cases, and the intervention effects of implemented quarantine and control measures.Methods: We develop a Susceptible, Un‐quanrantined infected, Quarantined infected, Confirmed infected (SUQC) model to characterize the dynamics of COVID‐19 and explicitly parameterize the intervention effects of control measures, which is more suitable for analysis than other existing epidemic models.Results: The SUQC model is applied to the daily released data of the confirmed infections to analyze the outbreak of COVID‐19 in Wuhan, Hubei (excluding Wuhan), China (excluding Hubei) and four first‐tier cities of China. We found that, before January 30, 2020, all these regions except Beijing had a reproductive number R > 1, and after January 30, all regions had a reproductive number R < 1, indicating that the quarantine and control measures are effective in preventing the spread of COVID‐19. The confirmation rate of Wuhan estimated by our model is 0.0643, substantially lower than that of Hubei excluding Wuhan (0.1914), and that of China excluding Hubei (0.2189), but it jumps to 0.3229 after February 12 when clinical evidence was adopted in new diagnosis guidelines. The number of un‐quarantined infected cases in Wuhan on February 12, 2020 is estimated to be 3,509 and declines to 334 on February 21, 2020. After fitting the model with data as of February 21, 2020, we predict that the end time of COVID‐19 in Wuhan and Hubei is around late March, around mid March for China excluding Hubei, and before early March 2020 for the four tier‐one cities. A total of 80,511 individuals are estimated to be infected in China, among which 49,510 are from Wuhan, 17,679 from Hubei (excluding Wuhan), and the rest 13,322 from other regions of China (excluding Hubei). Note that the estimates are from a deterministic ODE model and should be interpreted with some uncertainty.Conclusions: We suggest that rigorous quarantine and control measures should be kept before early March in Beijing, Shanghai, Guangzhou and Shenzhen, and before late March in Hubei. The model can also be useful to predict the trend of epidemic and provide quantitative guide for other countries at high risk of outbreak, such as South Korea, Japan, Italy and Iran.

Comparative population genomics offers an opportunity to discover the signatures of artificial selection during animal domestication, however, their function cannot be directly revealed. We discover the selection signatures using genome-wide comparisons among 40 mallards, 36 indigenous-breed ducks, and 30 Pekin ducks. Then, the phenotypes are fine-mapped based on resequencing of 1026 ducks from an F₂ segregating population generated by wild × domestic crosses. Interestingly, the two key economic traits of Pekin duck are associated with two selective sweeps with fixed mutations. A novel intronic insertion most possibly leads to a splicing change in MITF accounted for white duck down feathers. And a putative long-distance regulatory mutation causes continuous expression of the IGF2BP1 gene after birth which increases body size by 15% and feed efficiency by 6%. This study provides new insights into genotype–phenotype associations in animal research and constitutes a promising resource on economically important genes in fowl.

Tibetans live on the highest plateau in the world, their current population size is approximately 5 million, and most of them live at an altitude exceeding 3,500 m. Therefore, the Tibetan Plateau is a remarkable area for cultural and biological studies of human population history. However, the chronological profile of the Tibetan Plateau’s colonization remains an unsolved question of human prehistory. To reconstruct the prehistoric colonization and demographic history of modern humans on the Tibetan Plateau, we systematically sampled 6,109 Tibetan individuals from 41 geographic populations across the entire region of the Tibetan Plateau and analyzed the phylogeographic patterns of both paternal (n = 2,354) and maternal (n = 6,109) lineages as well as genome-wide single nucleotide polymorphism markers (n = 50) in Tibetan populations. We found that there have been two distinct, major prehistoric migrations of modern humans into the Tibetan Plateau. The first migration was marked by ancient Tibetan genetic signatures dated to approximately 30,000 years ago, indicating that the initial peopling of the Tibetan Plateau by modern humans occurred during the Upper Paleolithic rather than Neolithic. We also found evidences for relatively young (only 7–10 thousand years old) shared Y chromosome and mitochondrial DNA haplotypes between Tibetans and Han Chinese, suggesting a second wave of migration during the early Neolithic. Collectively, the genetic data indicate that Tibetans have been adapted to a high altitude environment since initial colonization of the Tibetan Plateau in the early Upper Paleolithic, before the last glacial maximum, followed by a rapid population expansion that coincided with the establishment of farming and yak pastoralism on the Plateau in the early Neolithic.